Preamble

This is a work in progress, started in the beginning of August, 2016. Since then, a lot of things have changed in the relatd R packages, most notably the package QCAGUI being merged into the package QCA to make the installation effort as smooth as possible and create a single user experience with both command line and graphical user interface in the same package.

Most of the examples work with the current stable version 2.6, which has some minor but important differences to versions before 2.5. For example, the function calibrate() has its default changed from type = "crisp" to type = "fuzzy". Examples still work with previous versions, but users should add type = "crisp" for the crisp calibration.

Also, some of the dialogs are changed in the current version, again with an example from the “Calibrate” menu. It’s dialog has been extensively improved, with a new and hopefully useful thresholds setter for the fuzzy calibration.

The structure of this book is different from the former user guide published in 2013. It will of course touch on the same topics and present the same package, but instead of organising chapters on the distinction between crisp, multi-value, and fuzzy sets, a better approach is to organise the book on QCA related analyses: necessity, sufficiency, parameters of fit, calibration etc. This structure is a first proposal, and readers are encouraged to make suggestions: as this is a work in progress, anything is subject to change until reaching a proper publication stage.

The book is more than a guide, but less than a complete theoretical material. This is valid for both R related information (chapter 1 being a very short introduction) and QCA information as well. There are entire books that cover both, and the purpose of this book is less about an in-depth discussion about R and QCA, but more about concentrating about how to perform QCA using R. It will briefly touch upon theoretical concepts (like necessity and sufficiency) but users are expected to already have an idea about what these concepts are.

Over the past three years, many new additions have substantially changed the shape of the QCA package: the graphical user interface, or drawing Venn diagrams up to seven sets, just to mention a couple of the most spectacular. However, the QCA functionality relies on the same minimization engine from version 0.6-5, so results are backwards compatible.

Topic related chapters will contain examples for all QCA variants (cs, mv and fs, also extentions) as well as detailed instructions how to perform each of the analyses using both command line and using the new graphical user interface.

There are not enough words to describe the amazing work of Yihui Xie and all the team of engineers from RStusio, who provide this public service and especially for the packages knitr, rmarkdown and bookdown which allow this form of HTML, PDF and ebook publication (among others).

The author thanks in advance for any feedback, as well as suggestions and likely corrections to the book content, sent to: dusa.adrian@unibuc.ro